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Cameras and image processing hardware are rapidly evolving technologies, which enable real-time applications for passenger cars, ground robots, and aerial vehicles. Visual odometry (VO) algorithms estimate vehicle position and orientation changes from the moving camera images. For ground vehicles, such as cars, indoor robots, and planetary rovers, VO can augment movement estimation from rotary wheel encoders. Feature-based VO relies on detecting feature points, such as corners or edges, in image frames as the vehicle moves. These points are tracked over frames and, as a group, estimate motion. Not all detected points are tracked since not all are found in the next frame. Even tracked features may not be correct since a feature point may map to an incorrect nearby feature point. This can depend on the driving scenario, which can include driving at high speed or in the rain or snow.

The need of weight reduction for fuel reduction and CO₂ regulations enforces the use of light-weight materials for structural parts also. The importance of reinforced composites will grow in this area. While the structural behavior and the simulation up to high strain-rate processes for those materials have been in the focus of investigation for many years, nowadays the simulation of high cycle fatigue behavior is getting important as well. Efficient fatigue analysis for metals was developed by understanding the microscopic behavior (crack nucleation and initiation) and bringing it to the macroscopic level by combining it with the matching test data (SN curves, etc.). Similar approaches can be applied to composite materials as well.

Automakers generally recommend not to weld structural parts after a vehicle crash, and these should be replaced as a whole part in case of a crash event. Sectioning of these members is also not recommended and use of the repair manual is mandatory in case of fracture of such parts. However, repair shops may not adhere to these instructions and use incorrect repair procedures on these members which would modify their strength properties. This study analyses the impact of welding structural members in a vehicle like the A-pillar which use Ultra-High Strength Steels (UHSS) for reducing the weight of the vehicle and improving the crashworthiness of the structure. The research conducted in this paper highlights the differences in the crash performance of a repaired vehicle as opposed to baseline injury values for the vehicle.

Geometry Tree is a term describing the product assembly structure and the manufacturing process for the product. The concept refers to the assembly structure of the final vehicle (the Part Tree) and the assembly process and tools for the final product (the Process Tree). In the past few years, the Geometry Tree-based quality process was piloted in the FCA US LLC assembly plants and has since evolved into a standardized quality control process. In the Part Tree process, the coordinated measurements and naming convention are enforced throughout the different levels of detailed products to sub-assemblies and measurement processes. The Process Tree, on the other hand, includes both prominently identified assembly tools and the mapping of key product characteristics to key assembly tools. The benefits of directly tying critical customer characteristics to actual machine components that have a high propensity to influence them is both preventive and reactive.

The Hybrid Cellular Automaton (HCA) algorithm is a generative design approach used to synthesize conceptual designs of crashworthy vehicle structures with a target mass. Given the target mass, the HCA algorithm generates a structure with a specific acceleration-displacement profile. The extended HCA (xHCA) algorithm is a generalization of the HCA algorithm that allows to tailor the crash response of the vehicle structure. Given a target mass, the xHCA algorithm has the ability to generate structures with different acceleration-displacement profiles and target a desired crash response. In order to accomplish this task, the xHCA algorithm includes two main components: a set of meta-parameters (in addition target mass) and surrogate model technique that finds the optimal meta-parameter values. This work demonstrates the capabilities of the xHCA algorithm tailoring acceleration and intrusion through the use of one meta-parameter (design time) and the use of Kriging-assisted optimization.

Simultaneous Localization and Mapping (SLAM) algorithms are extensively utilized within the field of autonomous navigation. In particular, numerous open-source Robot Operating System (ROS) based SLAM solutions, such as Gmapping, Hector, Cartographer etc., have simplified deployments in application. However, establishing the accuracy and precision of these ‘out-of-the-box’ SLAM algorithms is necessary for improving the accuracy and precision of further applications such as planning, navigation, controls. Existing benchmarking literature largely focused on validating SLAM algorithms based upon the quality of the generated maps. In this paper, however, we focus on examining the localization accuracy of existing 2-dimensional LiDAR based indoor SLAM algorithms. The fidelity of these implementations is compared against the OptiTrack motion capture system which is capable of tracking moving objects at sub-millimeter level precision.

Residual stress prediction arising from manufacturing processes provides paramount information for the fatigue performance assessment of components subjected to cyclic loading. The determination of the material model to be applied in the numerical model should be taken carefully. This study focuses on the estimation of residual stresses generated after deep rolling of cast iron crankshafts. The researched literature on the field employs the available commercial material codes without closer consideration on their reverse loading capacities. To mitigate this gap, a single element model was used to compare potential material models with tensile-compression experiments. The best fit model was then applied to a previously developed crankshaft deep rolling numerical model. In order to confront the simulation outcomes, residual stresses were measured in two directions on real crankshaft specimens that passed through the same modeled deep rolling process.

In order to explore approaches for improving object detection accuracy in intelligent vehicle system, we exploit super-resolution techniques. A novel method is proposed to confirm the conjecture whether some popular super-resolution networks used for environmental perception of intelligent vehicles and robots can indeed improve the detection accuracy. COCO dataset which contains images from complex ordinary environment is utilized for the verification experiment, due to it can adequately verify the generalization of each algorithm and the consistency of experimental results. Using two representative object detection networks to produce the detection results, namely Faster R-CNN and YOLOv3, we devise to reduce the impact of resizing operation. The two networks allow us to compare the performance of object detection between using original and super-resolved images. We quantify the effect of each super-resolution techniques as well.

Spot Welds are a category of welds used extensively in automotive structures, normally for metals. The fatigue analysis of such spot welds can be evaluated using (a) the Point 2 Point (P2P) method where a beam or bar is used to connect the 2 surfaces being joined, (b) a more modern approach where the 1D element is replaced with an “equivalent” brick element, or (c) a third approach that falls somewhere between where a “spider” and circular ring of elements, is used to represent the spot weld. In all 3 cases there is an assumption that the cross section is circular. For some specialist cases such as plastic connectors, the cross section is not circular so a new user defined weld is proposed. This paper will describe the approach that is based on the concept that a user generated tensor line can be used (equivalent to the theoretical Force/Moment to stress algorithms built into the P2P approach) along with special S-N curves create for different joint shapes.

Collaborative robots are more and more used in smart manufacturing because of their capability to work beside and collaborate with human workers. With the deployment of these robots, manufacturing tasks are more inclined to be accomplished by multiple humans and multiple robots (MH-MR) through teaming effort. In such MH-MR collaboration scenarios, the task distribution among the multiple humans and multiple robots is very critical to efficiency. It is also more challenging due to the heterogeneity of different agents. Existing approaches in task distribution among multiple agents mostly consider humans with assumed or known capabilities. However human capabilities are always changing due to various factors, which may lead to suboptimal efficiency. Although some researches have studied several human factors in manufacturing and applied them to adjust the robot task and behaviors.

This technical paper deals with design and manufacture of axial and orbital cutters for drilling large diameters holes in Carbon Fiber Reinforced Plastics (CFRP) / Titanium (TA6V) thick stack by means of an Automated Drilling Unit fixed on a drilling template. Creating tools that drill such stacked holes in a single operation is particularly difficult. The common strategies for tool designs designated to cutting composites stacked with metals as titanium include uncoated carbide, tools with a diamond coating applied by chemical vapor deposition (CVD). It is also question of what kind of drilling process should we use to achieve larger holes in minimum time. Therefore, axial drilling process with pilot, drill and ream steps find a competitor drilling process named orbital drilling which can achieve both operations in one step allowing then, burrless, free delamination, small and easy removable chips all with one tool being able to achieve different hole sizes.

In the high frequency range, the SEA method has been applied to air borne path with success to predict both internal and external sound environment. Nevertheless, structure-borne prediction is still at issue -especially for cars, in the range 200 to 2000 Hz- as results are widely dependant on subsystem partition and validity of various assumptions required by SEA. Experimental SEA test technique (ESEA), applied to car bodies, has brought to the fore that SEA power balanced equations could robustly describe structure-borne noise. To make ESEA predictive, the database of measured FRF is simply replaced and enlarged by synthesized data generated from a finite element (FE) model and a selected observation grid of nodes. This technique, called Virtual SEA (VSEA), has been presented at SAE/NVC 2003.

This paper presents preliminary result in a flexible fixture solution for airframe assembly comprising a modular steel framework called Box-joint and flexible tooling modules called Hexapods. The solution is comprises a framework that is screwed together instead of welding beams together, which enables re-building the framework when performing change-over in a more extensive reconfiguration. The Hexapods are parallel legged passive fixture stands that can change their configuration to facilitate easy setup in a change-over between handle different assemblies. A solution to configure the Hexapods manually is described. The investment cost can be kept low by using a metrology system to provide for high accuracy in the tool configuration process instead of using precision parts in the fixture system.

This paper is about the use of the Six Sigma Methodology, to solve variation problems in the manufacture area, at one of the Delphi Automotive Systems unit that manufacturer electrical harness. The DMAIC framework was followed, the improvements were done, eliminating the rots causes, and the use of Six Sigma methodology, was showed very efficient in solve problems. The methodology power, is in using a structured frame work, the DMAIC (Define-Measure-Analyze-Improve-Control), completing by quality quality tools (Pareto Chart, Five Why's, Cause and Effect Diagram) and statistical analyses, for example: variance analyses, hypotheses tests and Design of Experiments.

Reconditioning is one of the most important remanufacturing steps. For reconditioning metal cutting processes with low material removal rates are preferably used. Further requirements for these reconditioning processes are low attainable surface roughness and high flexibility. Brushing is a process that fulfills these requirements. In the past brushes were mostly used for cleaning and deburring. But with the development of new rotating brushing tools using grinding filaments even hardened materials have been machined. These grinding filaments made of polyamide with integrated hard grain like silicon carbide or aluminum oxide offer a wide range of new applications because a surface roughness Rz of less than 1 μm has been achieved. To attain repeatable results and to automate the process these brushing tools were integrated into a CNC-machining center.

This paper describes work being conducted by OC Robotics and Airbus to develop snake-arm robots to conduct assembly tasks within wing boxes - an area currently inaccessible for automation. The composite, single skin construction of aircraft structures presents new assembly challenges. Currently during box close-out it is necessary for aircraft fitters to climb into the wing box through small access panels and use manual or power tools to perform a variety of tasks. In future wing designs it may be that certain parts of the wing do not provide adequate access for manual assembly methods. It is also known that these manual interventions introduce health and safety concerns with their associated costs. Snake-arm robots provide a means to replace manual procedures by delivering the required tools to all areas of the wing box. Such a development has broader implications for aircraft design and assembly.

The key to efficient production of commercial aircraft is the development of a manufacturing system which allows the production of many different versions at the lowest possible cost and in the shortest possible throughput time. AIRBUS has accepted this challenge and implemented such a system in the form of a “moving line” at its Hamburg plant for the equipment installation of the A320 family. This new production system, which was designed in accordance with the flow principle, has been validated and optimised by means of a process simulation. With the application of this technique, the duration of the ramp-up phase has been decidedly shortened by early detection and reduction of faulty process sequences. In parallel with this development, the production and logistic system has been optimised with respect to the required target parameters.

Heijunka production, a core element of Toyota Motor Company's well-known Just-in-Time production methodology, was developed to deliver vehicle orders in the shortest lead time, with minimum inventory and maximum production efficiency. It achieves this by averaging (“leveling out”) production quantity and model. Adaptable to any production environment, the Heijunka production is an effective tool for industries with low-mix/low-volume production systems. In our case study, a manufacturer of interior subassembly items for commercial jets implemented Heijunka production and achieved significant improvement in inter-process inventory, lead time and productivity. Most notably, inter-process inventory was reduced to 20% in just five years.

Drilling is one of the most costly and labour-intensive operations in aircraft assembly. Rather than automating with expensive fixtures and precise machinery, our approach is to make use of standard low-cost robot equipment in combination with sensor feedback. The focus is to eliminate the sliding movement of the end-effector during the clamp-up, called the skating effect, and to keep the end-effector orthogonal to the surface, thus avoiding holes that are not perpendicular. To that end, force feedback is used for building up pressure to clamp up an end-effector to the work-piece surface prior to drilling. The system, including the planning of force parameters for each hole to be drilled, was programmed in DELMIA. The drilling was accomplished with the aid of an extension to the ABB Rapid language called ExtRapid, which is an XML-like code that is interpreted by the force feedback controller downstream in the process.

Recent changes in the aircraft production process have driven us, as a supplier of aircraft assembly equipment, to design innovative and modular manufacturing equipment that complies with modern specifications. The result is an all electric drilling and fastening machine that introduces new features while concurrently strengthening tried and true processes resulting in increased speed and efficiency. This technical paper describes the latest developments that have been integrated into an all electric fastening system which is fully fielded and successfully in production throughout the aircraft industry.